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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Wei Li Junfei Qiao Xiao-Jun Zeng College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China School of Computer Science University of Manchester Manchester U.K

ISBN: (纸本)9781467376839

This paper provides a complete solution for the problem how to accurately compute the similarity between fuzzy sets with Gaussian membership functions, which is a fundamental issue for the identification and simplification of FNNs. It is shown that there are three different types of similarities between a pair of Gaussian membership functions dependent on the relative positioning between the given pair of membership functions, and the accurate and detailed computing formulas are given in each type. A simulation example is given to compare the proposed accurate similarity analysis method with the existing approximation approaches and to show how much more accuracy can be obtained than the approximation one in terms of absolute percentage approximation error.

关键词： Fuzzy sets Fuzzy neural networks Shape Computational modeling Bismuth Knowledge discovery

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Corrigendum to “A Novel Improved Probability-Guided RANSAC Algorithm for Robot 3D Map Building”

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Journal of Sensors 2016年第1期2016卷

作者： Songmin Jia Ke Wang Xiuzhi Li Tao Xu College of Electronic and Control Engineering Beijing University of Technology Beijing 100124 *** Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 *** Engineering Research Center of Digital Community Ministry of Education Beijing 100124 *** School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang 453003 ***

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Reinforcement learning approach to learning human experience in tuning cavity filters

Reinforcement learning approach to learning human experience...

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IEEE International Conference on Robotics and Biomimetics

作者： Zhiyang Wang Jingfeng Yang Jianbing Hu Wei Feng Yongsheng Ou Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen P.R.China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen P.R.China Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Shenzhen P.R.China The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781467396769

Owing to the rapid development of the communication industry, various kinds of radio frequency components are in great demand and put into mass production. Among them, passive devices such as microwave cavity filters, duplexers and combiners have experienced fast and unexpected upgrades. However, the tuning process of these products, which is always manually operated, still seems hard to be automatically replaced or improved because of the difficulties in extracting human experience. In this study, we make deep investigations into some previous automatic cavity filter tuning solutions, especially the ones using intelligent algorithms. In addition, we propose the method of intelligent tuning based on the reinforcement learning algorithm which dynamically extracts the human strategies during the tuning process. The experimental results prove the powerful performance of reinforcement learning in mastering human skills.

关键词： Tuning Scattering parameters Fasteners Cavity resonators Games Robots Industries

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A new hybrid tracking strategy based on Pulse Coupled Neural Network

A new hybrid tracking strategy based on Pulse Coupled Neural...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Tao Xu Zhengyin Dong Xiuzhi Li Peng Zhang College of Electronic and Control Engineering Beijing University of Technology Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang China

ISBN: (纸本)9781467391054

Visual object tracking is a fundamental research topic in computer vision. In this paper, we proposed a novel hybrid tracking method based on Pulse Coupled Neural Network (PCNN) and Multiple Instance Learning (MIL). Most modern trackers may be inaccurate when the training samples are imprecise which causes drift. To resolve these problems, MIL method is introduced into the tracking task, which can alleviate drift to some extent. However, the MIL tracker may detect the positive sample that is less important. PCNN is different from traditional artificial neural networks, which can be applied in many image processing fields, such as image segmentation. So, the PCNN was employed as sample detector which can know the most important sample when training the classifier. Then, a more robust and much faster tracker is proposed to approximately maximize the bag likelihood function. Empirical results on a large set of sequences demonstrate the superior performance of the proposed approach in robustness, stability and efficiency to state-of-the-art methods in the literature.

关键词： Target tracking Neurons Visualization Object tracking Image segmentation Computer vision Computational modeling

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The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Service–oriented supply and demand network of enterprises

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Journal of Chemical and Pharmaceutical Research 2014年第6期6卷 1488-1495页

作者： Tai, Deyi Xu, Fuyuan Hu, Wei School of Management University of Shanghai for Science and Technology China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University China

To realize dynamic, open and multi supply-demand cooperation of Supply and Demand Network of Enterprises with Multifunction and Opening Characteristics (SDN), both the operational mode and implemented information platform were proposed, according to the restrictions existed in operational mode and service platform. A new operational pattern of SDN based on “full open, win-win cooperation” was propose, by bring service operator and platform provider in SDN. With “Decentralized resources centralize management, centralized resources dynamic service” as guidance, the information system framework of service-oriented SDN was proposed, the key technologies of SDN platform were discussed, the feature of service-oriented SDN were analyzed. Finally, a case of service-oriented SDN of small and medium-sized manufacturing enterprises was discussed. © 2014, Journal of Chemical and Pharmaceutical Research, All rights reserved.

关键词： Manufacture

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Relations' evolutionary in Supply and Demand Network of Enterprises with Multi-function and Opening Characteristics

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BioTechnology: An Indian Journal 2014年第12期10卷 6268-6279页

作者： Tai, Deyi Xu, Fuyuan Hu, Wei University of Shanghai for Science and Technology School of Management China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University China

There are three relations exist in Supply and Demand Network of Enterprises with Multifunction and Opening Characteristics (SDN) that are competition, cooperation and neutrality relations, which's evolutionary will effects the stability of SDN. To reveal the evolution process and interactive of the three relations among enterprises of SDN, an evolutionary game model in SDN was build to solve the problem of real cooperative strategy selection. The model of enterprises relations evolutionary was established base on evolutionary game theory, and analyzed with numerical simulations in MATLAB. The research shows that the strategy selection of cooperation, competition and neutrality in SDN were mainly determined by transferable and non-transferable incomes. Enhancing supervision and punishment to opportunistic behavior and malicious competition in SDN, will improve enterprises' relations from neutrality to cooperation. © Trade Science Inc.

关键词： Competition

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Modeling and simulation of competition-cooperation and neutrality relations in SDN enterprises

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Journal of Chemical and Pharmaceutical Research 2014年第5期6卷 1714-1724页

Besides competition and cooperation, there also have neutrality relations, which is noncompetition and noncooperation, exists in Supply and Demand Network of Enterprises with Multi-function and Opening Characteristics (SDN). To reveal the evolution of cooperation, competition and neutrality relations among enterprises in SDN, an evolutionary model on node relations in SDN was build to solve the problem of real cooperative strategy selection. Base on evolutionary game theory, an enterprises relations evolutionary game model was established, and analyzed with numerical simulations in MATLAB. The results show that transferable and non-transferable incomes determined the choice of cooperation, competition and neutrality strategy. Opportunistic behavior and malicious competition exited in SDN, which reduced the overall revenue and destroyed the stability of SDN. Enhanced supervision and punishment in SDN will improve enterprises’ relations from neutrality to cooperation. © 2014, Journal of Chemical and Pharmaceutical Research. All right reserved.

关键词： Competition

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An adaptive Differential Evolution algorithm for sewer networks design

An adaptive Differential Evolution algorithm for sewer netwo...

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World Congress on Intelligent control and Automation (WCICA)

作者： Changfen Liu Honggui Han Chao Wang Junfei Qiao Beijing University of Technology Beijing CN College of Electronic and Control Engineering Beijing Key Laboratory of Computational Intelligence and Intelligence System

A newly introduced Self-adaptive Differential Evolution algorithm via Generalized Opposition-Based Learning (SDE-GOBL) is applied to optimal design of two sewer networks. Every chromosome consists of the information of network layout. Select a feasible design which satisfies the constraints of velocity, slope and proportional water depth to get optimal cost through the algorithm. Two sewer optimization problems in which the pipe diameters are considered as the decision variables are solved by the SDE-GOBL algorithm. Comparisons with the previous works are made and the results show that the proposed algorithm performs better in terms of solution quality and efficiency.

关键词： Vectors Algorithm design and analysis Sociology Statistics Optimization Genetic algorithms Pipelines

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Direct adaptive neural network control for wastewater treatment process

Direct adaptive neural network control for wastewater treatm...

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World Congress on Intelligent control and Automation (WCICA)

作者： Wei Zhang Jun-fei Qiao College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing China

In this paper, a direct adaptive neural network control (DANNC) method is developed to deal with the multi-variable (dissolved oxygen concentration and nitrate concentration) tracking control problem in wastewater treatment processes (WWTPs), which avoids the perplex issue of establishing the plant model of WWTP and has the excellent adaptive ability. The DANNC system is composed of neural controller and compensation controller. The neural controller is employed to approximate an ideal control law, and the compensation controller is designed to offset the network approximation error. The controller parameters' adaptive laws are deduced by the Lyapunov theorem. Simulation results, based on the international benchmark simulation model No.1 (BSM1), show that the control accuracy and dynamic performance of the DANNC method are improved nicely.

关键词： Effluents Mathematical model Neural networks Biological system modeling Inductors Process control

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